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The frequency of extreme events is increasing on a global scale due to various factors, accounting for natural disasters such as landslides, floods, and droughts. The Heilongjiang province, which is agriculturally important for China, has suffered from several extreme rainfall events in the past as a high-latitude plain region. Analysis of historical rainfall characteristics of the Heilongjiang region helps to understand and predict the behavior of extreme rainfall events and provides a reference for reducing agricultural economic losses. Precipitation data from 1974 to 2017 is selected to estimate whether rainfall series in Heilongjiang obey the Gumbel-Logistic Model. We compared the Gumbel-Logistic Model based on the data length of 5 years, 10 years, and 20 years with the original 44-year data to determine the appropriate data partition length and explore the reasons for errors. Combining the empirical frequency and KS test, this paper concludes that the proposed model is appropriate for the representation of the joint distribution of monthly extreme rainfall and annual rainfall. The proposed model improves the rainfall assessment of these two positively correlated variables in Heilongjiang. Univariate and bivariate return periods and correlation coefficients are derived as the basis for assessing the risk of extreme rainfall. The proposed model obtained from the 5-year data length has the largest error, while the distribution curve is progressively smoother as the data length increases. [ABSTRACT FROM AUTHOR]

This paper analyzes the correlation between precipitation and deforestation and trends in the Brazilian Amazon Biome from 1985 to 2021 using rain gauge measurements. A total of 187 stations were selected after filtering time series with less than 10% of missing data. Deforestation data was acquired using the MapBiomas dataset. Results show that deforestation rates vary across different locations and may be influenced by various factors. The analysis also found significant negative correlations between precipitation and deforestation, with a range of − 0.49 to − 0.33, as well as significant positive correlations, with a range of 0.34 to 0.57. These findings underscore the importance of continued monitoring of precipitation patterns in the region and the urgent need for measures to mitigate deforestation, which is critical for the hydrological cycle of the region. The highest deforestation rates and values were found between latitude 0 and − 12.5, where the arc of deforestation lies. Additionally, this study found a significant negative correlation between precipitation patterns and deforestation, indicating that deforestation led to a reduction in rainfall in the region. [ABSTRACT FROM AUTHOR]

Under global warming and climate change (CC), the vulnerable piece of land is India's Eastern-Himalayan-Region (EHR), where millions' livelihood activities are at risk. Quantifying the degree of CC-induced vulnerability over the highly climate-sensitive mountain zone is challenging due to data inadequacy. This paper attempted to assess the CC perception of kiwifruit growers under EHR and the impact of CC on its cultivation. Perceived and scientific data were used for accurate decision-support information. The climatic variables of two locations were analyzed for trend using Mann–Kendall's test. Results suggested that the rainfall trend was found non-significant for both locations, but there was a negative trend during winter for Pasighat and during all seasons for Itanagar. Maximum temperature exhibited an increasing trend for annual, and minimum temperature showed an increasing trend across seasons for the Pasighat region. For the Itanagar region, the maximum temperature was found to have a significantly increasing trend in all seasons, while the minimum temperature showed an increasing trend during winter and annual seasons. Morning relative humidity showed an increasing trend for annual data for Pasighat, while annual evening relative humidity was significantly increased for Itanagar. The study shows that the indigenous farming communities were following shifting cultivation and diversifying their traditional agriculture to kiwifruit cultivation as an adaptation strategy. The community had a clear perception of CC trends and an inadequate perception of the impact on agriculture, therefore, engaging indigenous communities and other stakeholders to postulate a comprehensive adaptation and mitigation strategy for CC. [ABSTRACT FROM AUTHOR]

Understanding the future patterns of precipitation behaviour in unique geographical areas, largely determined by their orography and local scale, can help lay the foundations for a new precipitation model for the design of the city's main urban drainage infrastructures (intensity-duration-frequency curves, mathematical functions that relate precipitation intensity to duration and frequency of occurrence, hereafter IDF, for the short-, medium- and long-term future). This will definitely contribute to the improvement of the city's resilience to the effects of climate change. In this paper, the projections of a subset of climate change models from both the sixth phase of the Coupled Model Intercomparison Project (CMIP6; with a total of 5 simulations) and Euro-CORDEX (for a set of 51 simulations) have been adjusted to the municipality of Alicante (in the southeast of Spain), using the Climadjust tool (climadjust.com). These projections contain different climatic variables. The rainfall variable has been used to derive a new framework of boundary conditions to help design more resilient infrastructure for torrential rainfall events and urban flooding. The projections corresponding to three climate change scenarios (CMIP6: SSP1-2.6, SSP2-4.5, SSP5-8.5; and Euro-CORDEX: RCP2.6, RCP4.5, RCP8.5) are considered with daily resolution and, by applying statistical techniques of temporal disaggregation (by means of a cascade model), hourly (and sub-hourly, reaching 30-min resolution) disaggregation. The results at hourly and 30-min resolutions are used to construct IDF curves of future climate, grouped into short-term (years 2015 to 2040), medium-term (years 2041 to 2070) and long-term (years 2071 to 2100) sub-scenarios. The selected future climate IDFs for an adverse climate change scenario (SSP2-4.5 and SSP5-8.5) show increases in rainfall intensities, higher the shorter the rainfall duration, for return periods greater than or equal to 25 years, whereas for return periods under 25 years the current IDFs can be representative of future scenarios. Current calculations and future projection of the torrentiality index for severe climate change scenarios, as well as the climate change factors, show an increase in the frequency and magnitude of the heaviest rainfall. This fact corroborates the hypotheses of greater general torrentiality in future rainfall in this specific area of the Spanish Mediterranean coast. [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) is a major influence on interannual variability of rainfall in stations in the tropical southwest Pacific. Predictions of seasonal rainfall, especially a season or two ahead, are of great value to these countries. This paper therefore examines the correlations over ~ 60 years between seasonal rainfall and 8 ENSO indicators at 16 island stations, allowing for lead times. The results show the influence on rainfall of the position and movement of the South Pacific Convergence Zone (SPCZ) during ENSO events, and that the Southern Oscillation Index (SOI), the sea surface temperature anomaly in the central Pacific (Niño 3.4), and the warm water volume in the eastern Pacific (WWV1) have longer lead times compared to most other ENSO indicators. These indicators can therefore be used with confidence in SCOPIC, a widely used statistical tool for prediction of seasonal rainfall. (As global climate models generally have systematic errors in their depiction of the SPCZ, they cannot yet be used directly to reliably predict seasonal rainfall in this region.) For several sites near the SPCZ, we find that a moderately good forecast of rainfall in both spring and summer can be made from indicators measured in June–July (i.e., 3–6 months in advance.) [ABSTRACT FROM AUTHOR]

The Western Ghats (WG) is one of the important biodiversity hotspots and rainfall intense regions in south Asia. In this paper, the long-term trend analysis is carried out during southwest monsoon rainfall over different latitudinal regions of the WG. Further, the gridded daily rainfall data (0.25 × 0.25 spatial grid resolution) is classified into six intensity bins: dry, low, moderate, heavy, very heavy, and extreme, from 1951 to 2015. A detailed trend and variability analysis of rainfall and its frequency in different intensity bins along with their relative contribution were carried out. The results of different rainfall intensity bins depict that the moderate and low intensity bins contribute a maximum share in seasonal rainfall with 45% and 20%, respectively, from the 30% and 50% rainy days in all the regions. Heavy and very heavy intensity bins together contribute about 30% of the seasonal rainfall from about 9% rainy days. Extreme intensity bin recorded an alarming share of 6% with only 1% rainy day occurrences. In general, the relative contribution shows an ascending pattern of moderate, low, very heavy, heavy, extreme, and dry intensity bins. A decreasing trend in rainfall was observed in heavy and very heavy intensity bins, while other intensity bins illustrated mixed trends in different study regions. Extreme rainfall events marked a major shift upward in the WG region during the study period. Overall, our result portrays a negative trend in rainfall during the southwest monsoon season over all the study regions during the study period. [ABSTRACT FROM AUTHOR]

Estimating precipitation over large spatial areas remains a challenging problem for hydrologists. Satellite-based remote sensing rainfall products have the advantage of large-scale synchronous coverage, but the reliability of their inversion still needs to be improved. Correcting the bias of satellite-based precipitation estimates (SPEs) is a major challenge in applications such as environmental modeling, hydrology, and water resource management. In this paper, a new bias correction method—a Gaussian process regression (GPR) model method based on rain intensity classification—is proposed to improve the accuracy of a satellite precipitation product—the Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run (FR) product—at the daily scale in the Guangdong-Hong Kong-Macao Greater Bay Area. By comparing the effects of the proposed method with those of other existing classical correction methods, namely, quantile mapping (QM), the support vector machine (SVM) approach and direct GPR, it is found that all four methods improve the accuracy of the FR product to varying degrees. GPR based on rain intensity classification has the best effect of FR product improvement, with the CORR increasing from 0.55 to 0.59, the RMSE ranging from 14.37 to 12.79 mm/day, and the BIAS ranging from − 0.14 to 0.03 during the validation period. GPR without rain intensity classification also yields good results, with the QM and SVM methods being the least effective. [ABSTRACT FROM AUTHOR]

Rainfall onset dates (ROD), rainfall cessation dates (RCD) and length of rainy season (LRS) are crucial for crop production and food security in Eastern Africa yet scantily documented. This paper seeks to investigate the spatial patterns of these parameters. Data used are Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2.0) and National Oceanic and Atmospheric Administration (NOAA) gridded temperature. Threshold of 1 mm for rainy day, 20 mm over 5 days with at least 3 rain days and dry spell not exceeding 7 days in the next 21 days were used to determine RODs. The Potential Evapotranspiration (PET) and Water Balance (WB) criteria were computed to determine RCDs. The differences between ROD and RCD were used in calculating LRS. The results showed early rainfall cessation over more than 30 counties in Kenya lead to shortened rainy season by 10–20 days during MAM season. Similarly, 20–40 days early onset dates are observed in most counties in upper Nile, Unity, and Jonglei states in South Sudan, while 20–40 days delayed rainfall onset was observed in Khartoum and southern parts of Nile state western Darfur, eastern and Aljazeera states in Sudan, most parts of Ethiopia and Eritrea districts during JJA season. Highlands of western and Nyanza region in Kenya, most parts of Uganda observed rainfall onset by March and no sign of cessation before November. Early cessation over northern Uganda districts was behind shortened LRS, furthermore, the early RODs over western and southwestern Uganda districts increased LRS. Prolonged dry conditions over northern Sudan, southeastern parts of South Sudan, northern Kenya, central Somalia, northern Darfour, Kordofan and northern parts of Sudan exacerbated by significant delayed onset and early cessation of rainfall. These findings are important for rain-fed agricultural planning and food security in the IGAD region of Eastern Africa. [ABSTRACT FROM AUTHOR]

Rainfall in the Moist Tropical Caribbean Region (MTCR) in Costa Rica occurs practically throughout the year, with the quarters June–August (JJA) and December–February (DJF) concentrating over 70% of annual rainfall. Contrarily, in March–April and September–October, it rains below 100 mm per month. This seasonal rainfall behavior makes the region ideal for producing bananas (Musa spp.) and pineapple (Ananas comosus) for export (10% and 8% of total exports in 2021, respectively). A national-scale study determined that agriculture in the MTCR is one of the most vulnerable sectors to climate changes. However, the climate in this region has been poorly studied so far. This research analyzed the spatial and temporal variability of annual, monthly, and seasonal (DJF, JJA, SO) rainfall in the MTCR and how they change in the study period based on quality-checked series of daily rainfall from 28 weather stations in two periods: 1985–2009 and 1997–2019. The results show that rainfall regimes in the region are variable in space and throughout the year, with peaks occurring close to the mountain range and minimum values close to the coast. Trends were statistically significant in the period 1985–2009 with a predominance of significant positive trends in DJF and significant negative trends in SO. No significant trends (positive or negative) were observed in the period 1997–2019. JJA rainfall has uneven regional distribution and presents a positive and significant trend in the mountain region. This paper contributes to filling the knowledge gap in rainfall seasonality, variability, and trends in a region where banana and pineapple commercial plantations are fundamental to the country's economy thus providing information to decision-making in the agri-food sector to reduce the negative impacts of changing rainfall regimes. [ABSTRACT FROM AUTHOR]

In this paper, Japan Meteorological Agency (JRA-55) reanalysis and observational rainfall datasets from the National Climate Center (NCC) of China, as well as satellite datasets from the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Project (GPCP), and International Satellite Cloud Climatology Project (ISCCP), are used. The correlation coefficient and fast Fourier transform (FFT) low-pass filter are also used, in order to reveal the interdecadal decrease in autumn rainfall in Southeast China (SEC) after 1990. The close and robust relationship between the interdecadal variation in autumn rainfall in SEC and sea surface temperature (SST) in the tropical Pacific is investigated. The most significant and stable region of correlation is located in 10° S–10° N, 160° E–160° W, in which there also exists interdecadal warming after 1990. Furthermore, the interdecadal warming of SST can induce Gill responses of the atmosphere: a cyclone anomaly is produced on each side of the equator in the lower troposphere, with a westerly anomaly to the west of the dateline, and an anticyclone anomaly is produced in the upper troposphere. In particular, the cyclone anomaly on the northern side of the equator is located in the Northwest Pacific (NWP), and its ambient northerly airflow weakens meridional water vapor transport, as well as the local descending motion and low-troposphere divergence, in favor of the interdecadal decrease in SEC rainfall after 1990. In addition, the sensitive experiments with ECHAM-5.4 model also confirm that the interdecadal warming in the region (10° S–10° N, 160° E–160° W) would motivate the atmospheric Gill response and thereby cause the sinking motion in SEC and support the interdecadal decrease in autumn rainfall in SEC. [ABSTRACT FROM AUTHOR]

Climate change may cause adverse impact on agricultural production that could jeopardize food availability and security. In this paper, we investigate how changes in mean values and variability of weather variables may affect rice yield using panel data for 30 districts of Tamil Nadu State from 1971 to 2018. We estimate a fixed-effects regression model with panel-corrected standard errors. Results show that rainfall and temperature have a statistically significant impact on rice yield. Furthermore, weather variability, measured as standard deviations of temperature and rainfall, has a negative effect on rice yields. We use the Coupled Model Inter-comparison Project-5 outputs and dynamically downscaled the weather outputs using the regional climate model. The results of the climate model showed that the rise in temperature and disruptions in rainfall patterns including both excessive and deficient rainfall events in Tamil Nadu will continue in the future under different climate scenarios. Projected changes in the weather variables are likely to decrease rice yield in Tamil Nadu from 0.7 to 6.3% under the low emission scenario and 4.1 to 20.1% in the high emission scenario during 2022–2050 (relative to 1971–2018). These projections have implications for the planning and targeting of climate adaptation technologies such as drought-tolerant and flood-tolerant varieties to lessen the adverse impact of weather variability due to climate change in the future. [ABSTRACT FROM AUTHOR]

The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth's land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted. [ABSTRACT FROM AUTHOR]

B Correction to: Theoretical and Applied Climatology b https://doi.org/10.1007/s00704-022-04168-4 The affiliation of one of the authors (Pranaya Diwate) has been wrongly mentioned in the paper. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. [Extracted from the article]